Impact of signal intensity normalization of MRI on the generalizability of radiomic-based prediction of molecular glioma subtypes.

ABSTRACT:

Objectives

Radiomic features have demonstrated encouraging results for non-invasive detection of molecular biomarkers, but the lack of guidelines for pre-processing MRI-data has led to poor generalizability. Here, we assessed the influence of different MRI-intensity normalization techniques on the performance of radiomics-based models for predicting molecular glioma subtypes.

Methods

Preoperative MRI-data from n = 615 patients with newly diagnosed glioma and known isocitrate dehydrogenase (IDH) and 1p/19q status were pre-processed using four different methods: no normalization (naive), N4 bias field correction (N4), N4 followed by either WhiteStripe (N4/WS), or z-score normalization (N4/z-score). A total of 377 Image-Biomarker-Standardisation-Initiative-compliant radiomic fe

SUBMITTER: Foltyn-Dumitru M 

PROVIDER: S-EPMC10957611 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature